If you want to learn about artificial intelligence (AI), a great starting point is to read some of the best artificial intelligence books. You can also learn AI by enrolling in a college program, bootcamp, or online course. However, if you are not sure if you will like the topic, or you just want a basic understanding of it, checking out the best books for artificial intelligence is ideal.
Some AI is used to develop artificial brains or AI robots, while other AI applications analyze online behavior and optimize ecommerce products. AI powers many programs and services in our daily life, making it a driving force in the world. In this article, you can find the best books to learn artificial intelligence and some tips for choosing AI books.
How Can I Choose the Best Books for Artificial Intelligence and Machine Learning Engineers?
If you have zero knowledge in this area, then you need to choose books that explain the fundamentals of artificial intelligence and an overview of machine learning (ML). You should also read about other related topics, like data science and deep learning.
If you do have some knowledge of AI, then you should consider what you are interested in learning before choosing a book. Do you like neural networks or do you want to get a more general overview of machine learning? Maybe you want to create intelligent machines or study deep learning techniques. Consider what you want to learn about AI and pick a book on that topic.
Tips for Choosing the Best Artificial Intelligence Books
- Decide your learning goal. Think about what you are trying to learn and what experience you would like to gain. Having a clear learning goal will make it easier for you to choose the right book in less time.
- Research the AI topics you want to learn. Researching AI topics will help you learn more about them and fine-tune your learning goals. Also, the more information you have, the better understanding you will have of what kind of book you will need.
- Read summaries and research the books. Read the summary of a book and see if it’s appealing to you. Try to understand, from the provided information, whether the book has what you are seeking. Research and explore what the book offers, and this will help you decide if the book is for you. Seek books with a concise overview.
- Read reviews. Using a book’s reviews, you can find out more about what kind of information it has. The reviews will share whether the book is good or bad which you can use to ultimately decide if it suits your needs. Try searching for keywords within the reviews to check if the book covers a certain subject.
- Ask an expert. If you are just starting in the AI field then one of the best ways to find a good artificial intelligence book is to ask someone who is working in the field. Ask them which books they would read if they were just starting out in this field. Asking experts for advice is always a good idea because they can share what helped them.
The 10 Best Artificial Intelligence Books: An Overview
| Name | Publisher | Topics Covered |
|---|---|---|
| AI Superpowers: China, Silicon Valley, and the New World Order | Harper Business | AI competition, technological power, AI superpowers |
| Applied Artificial Intelligence: A Handbook For Business Leaders | TOPBOTS | AI platform, AI business cases, business leadership |
| Artificial Intelligence For Dummies | For Dummies | History of AI, machine learning, autonomous vehicles |
| Artificial Intelligence: A Modern Approach Fourth Edition | Pearson | Artificial intelligence, machine learning, deep learning |
| Artificial Intelligence: The Insights You Need from Harvard Business Review | Harvard Business Review Press | Blockchain, cyber security, AI |
| Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World | Harvard Business Review Press | Business strategy, digital transformation, AI in business and operating models |
| Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems First Edition | O’Reilly Media | Machine learning, intelligent systems, neural net architectures |
| Human Compatible: Artificial Intelligence and the Problem of Control | Penguin Books | AI-systems, reinforcement learning, machine learning |
| Machine Learning (in Python and R) For Dummies | Wiley | Machine learning, R language, Python language |
| Make Your Own Neural Network | CreateSpace Independent Publishing Platform | Neural network, machine learning, deep learning |
The 10 Best Artificial Intelligence Books: A Closer Look
Artificial intelligence is a topic that’s closely related to neural networks, deep learning and machine learning. Therefore, our list of the best books for artificial intelligence covers these topics.
Some of the books on the list are technical and require advanced knowledge, while others are for beginners and a wider audience. With these books, you will gain a better understanding of machine learning principles, deep learning models, and the business applications of AI.
1. AI Superpowers: China, Silicon Valley, and the New World Order
- Author: Kai-Fu Lee
- Best for: People interested in the business economy and global economy
Many experts already believe that artificial intelligence will replace the workforce and have a devastating effect on blue-collar professions. However, Lee believes that Chinese and American AI will have a significant influence on white-collar occupations. In his book, he presents a clear picture of which occupations and business processes will be affected, and when.
2. Applied Artificial Intelligence: A Handbook for Business Leaders
- Author: Mariya Yao, Adelyn Zhou, and Marlene Jia
- Best for: Business leaders, executives, entrepreneurs, and practitioners
This book is a step-by-step playbook for business executives who want to use machine intelligence to improve their firms’ efficiency. This is a comprehensive and practical guide for entrepreneurs who like to drive innovation by merging data, technology, and design. It is for people who like to tackle real-world challenges on a large scale.
There are other technical books on the market that dive into the details and intricacies of modern algorithms. However, this book doesn’t burden you with technical coding tasks or endless business generalizations and, instead, helps you gain insight into how to make better business decisions. It is a balance between business and AI initiatives.
3. Artificial Intelligence For Dummies
- Author: John Paul Mueller and Luca Massaron
- Best for: Beginners and anyone who wants to understand the basics of AI technology
This is an informative read about the AI tools you can use and what kind of challenges those tools can solve. It’s educational and approachable, without being patronizing. It offers a solid understanding of what AI can do and what its limitations are. It is a less than hundred-page machine learning book and is, overall, a good starting book to get to know AI.
4. Artificial Intelligence: A Modern Approach, Fourth Edition
- Author: Stuart Russell and Peter Norvig
- Best for: Undergraduate and graduate-level studies
This book is recognized by some as the most popular AI textbook in the world. It covers topics ranging from probabilistic programming, robotics, natural language processing, problem-solving, deep learning, ML, AI, and communication. It is used by professors in universities and is one of the best books that can introduce you to the theory and practice of AI.
5. Artificial Intelligence: The Insights You Need from Harvard Business Review
- Author: H. James Wilson, Thomas H. Davenport, Andrew McAfee, and Erik Brynjolfsson
- Best for: Business and company leaders
AI and machine learning are already transforming business and society, from making quicker, smarter judgments to automating routine labor and allowing machines to respond to emotions. If you want your company to become successful, you have to compete with other companies that use artificial intelligence, or yours will become obsolete. This book explains how to do that.
6. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World
- Author: Marco Iansiti and Karim R. Lakhani
- Best for: Business people, entrepreneurs, investors
This book is a guide for business leaders that explains how to manage, transform, grow, and control your business in today’s digital age. It explains the collisions between AI-driven and traditional firms, but also how AI helped Google, Amazon, Microsoft, and Apple to rise. It presents the perspective of the big picture of AI and ML happening around the world.
7. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems First Edition
- Author: Aurélien Géron
- Best for: Intermediate and advanced audiences with knowledge in deep learning, Python, and statistical knowledge
This book has a hands-on approach to learning by doing. It offers snippets of code, with complete examples you can find within a Git repository that provides detailed explanations. The book has an excellent introduction to the field of machine learning and deep neural nets.
It introduces concepts and practical tools for building intelligent systems for solving all kinds of problems using Python frameworks and libraries like Scikit-Learn, Keras, and Tensorflow 2.0. You will also find several training models like ensemble methods, decision trees, and vector machines.
8. Human Compatible: Artificial Intelligence and the Problem of Control
- Author: Stuart Russell
- Best for: Non-technical audience and people working in the AI field
In Human Compatible, Russell explores the idea of human and machine intelligence. He tries to explain the fate of the human race when confronted with machines that can outwit us. The book covers machine roles in human lives, and the benefits and discoveries that artificial intelligence can offer.
Despite this, it also mentions what the possible misuse of the same technology could cause, from deadly autonomous weapons to viral sabotage. It is an overview of the imposing conflict between humans and machines and how to overcome it.
9. Machine Learning (in Python and R) For Dummies
- Author: John Paul Mueller and Luca Massaron
- Best for: Beginners in ML and AI that have some knowledge in Python and R
This book is an excellent starting point for anybody interested in learning more about ML, AI, programming, and data. In this book, you can find how to use Python and R language to execute data analysis and perform pattern-oriented jobs. The small tasks this book offers can help readers learn how to use ML for web searches, online advertisements, and fraud detection.
10. Make Your Own Neural Network First Edition
- Author: Tariq Rashid
- Best for: Total beginners in neural networks but with prior knowledge in Python and math skills
The Make Your Own Neural Network book is a practical guide to building a neural network using the Python computer language. It offers great coverage of machine learning principles, mathematics, and gradient descent, and lays out everything in a clear and easy-to-understand manner. This is one of the best books that explain the main fundamental concepts of neural networks.
Alternative Ways to Learn Artificial Intelligence
Some alternative ways to learn about artificial intelligence and intelligent technology are through AI online courses and AI bootcamps. Although a book can be a comprehensive guide to a particular matter, it does not always offer all the answers. When it comes to building practical applications, you will have questions that a book can’t answer.
For example, if you want to create smart machines, it is better to have someone to guide you and help you solve the issues you are facing. You can also receive this guidance by studying in an artificial intelligence degree program.
Is Learning Artificial Intelligence Worth It?
Yes, learning artificial intelligence is worth it. According to the Bureau of Labor Statistics (BLS), there are around 33,000 jobs in computer and information science, and people in this field earn an average salary of $126,830 a year. BLS predicts that employment for computer and information scientists will grow to 22 percent by 2030.
It is important to learn aspects of machine learning, deep learning, and how human intelligence works if you want to understand AI. The best method for doing that is reading some of the best artificial intelligence books detailed above. We also recommend that you check out other authors not listed, such as Ernest Davis, Gary Marcus, Jeff Heaton, and Ian Goodfellow.
Best Artificial Intelligence Books FAQ
Some of the best artificial intelligence software are Google Cloud Machine Learning Engine, Azure Machine Learning Studio, TensorFlow, and H2O.AI. AI Software comes in four different types. AI software can be in the form of artificial intelligence platforms, chatbots, deep learning software, and machine learning software.
Yes, you can self-study artificial intelligence. A computer science degree covers some artificial intelligence and machine learning techniques, but you don’t need a degree to work in the field. Even if you have no prior engineering experience, you can learn artificial intelligence from home and begin putting your knowledge into practice by creating simple machine learning solutions.
A shorter AI classification would identify three types of artificial intelligence: narrow AI, general AI, and super AI. A broader AI classification considers whether the AI is reactive, has a limited memory, or is self aware. These aspects can identify whether AI is considered artificial narrow intelligence (ANI), artificial general intelligence, or artificial super intelligence (ASI).
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Yes, AI can be difficult to learn, especially if you have no programming experience. You need to build your foundational knowledge and then hone your skills. Then, you need to learn Python or R language and have a great in-depth knowledge of machine learning and deep learning. It’s hard, but, with the right resources, you can do it.
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